Jobby Jacob Headshot

Jobby Jacob

Associate Professor

School of Mathematics and Statistics
College of Science

585-475-5146
Office Hours
Fall 2022: Tu.We.Th.: 9:30 - 10:30 am, and by appointment.
Office Location

Jobby Jacob

Associate Professor

School of Mathematics and Statistics
College of Science

Education

BS, Bharata Mata College (India); MS, Indian Institute of Technology (India); Ph.D., Clemson University

585-475-5146

Personal Links
Areas of Expertise

Select Scholarship

Invited Keynote/Presentation
Jacob, Jobby. "Rankings (ordered colorings) of Graphs." Math. Colloquium. Hobart and William Smith Colleges. Geneva, NY. 11 Apr. 2019. Keynote Speech.
Jacob, Jobby. "L(h,k) labelings and rankings of some dense graphs." Thirty-second Midwest Conference on Combinatorics, Cryptography, and Computing. University of Minnesota. Duluth, MN. 6 Oct. 2018. Conference Presentation.
Jacob, Jobby. "Graph labeling based on distance one and distance two." MAA Seaway Section Meeting. SUNY. Brockport, NY. 13 Apr. 2018. Conference Presentation.
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Journal Paper
Dobosh, Korrine, Samuel Kennedy, and Jobby Jacob. "On the rank number of the Cartesian product Km X Kn for small values of m." Journal of Graph Labeling. (2018): 1. Web.
Jacob, Bonnie and Jobby Jacob. "lp-optimal rankings and max-optimal rankings are different." Graphs and Combinatorics. (2017): 1473–1483. Print.
Jacob, Jobby and Christopher Wood. "A complete L(2,1) span characterization for small trees." AKCE International Journal of Graphs and Combinatorics.. (2015): 26-31. Print.
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Currently Teaching

MATH-241
3 Credits
This course is an introduction to the basic concepts of linear algebra, and techniques of matrix manipulation. Topics include linear transformations, Gaussian elimination, matrix arithmetic, determinants, vector spaces, linear independence, basis, null space, row space, and column space of a matrix, eigenvalues, eigenvectors, change of basis, similarity and diagonalization. Various applications are studied throughout the course.
MATH-251
3 Credits
This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to real-world problems. A statistical package such as Minitab or R is used for data analysis and statistical applications.
MATH-645
3 Credits
This course introduces the fundamental concepts of graph theory. Topics to be studied include graph isomorphism, trees, network flows, connectivity in graphs, matchings, graph colorings, and planar graphs. Applications such as traffic routing and scheduling problems will be considered.